Over-Reach Detector
Detect when AI code changes exceed declared task scope (MCP server).
Que pouvez-vous faire avec Over-Reach Detector ?
declared_files: list of fnmatch globs (e.g.["docs/*.md", "tests/*.py"])declared_categories: subset of["tests", "docs", "infra", "config", "code"]actual_files: list of file paths the AI modifiedoutput_format:"json"(default) or"markdown"status:in_scope(within declared scope) |over_reach(reported mismatch) |emptyfile_overreach: files not matching any declared globcategory_overreach: inferred categories outside the declared set
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
over-reach-detectorclaude mcp add over-reach-detector -- uvx over-reach-detector==0.0.6
{
"mcpServers": {
"over-reach-detector": {
"command": "uvx",
"args": [
"over-reach-detector==0.0.6"
]
}
}
}
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
Over-Reach Detector (MCP server)
Detect and report when AI coding agents change files outside their declared task scope. Designed to plug into Cursor, Claude Code, and other MCP-compatible AI coding agents via the standard stdio transport.
Compares two things:
- Declared scope — the files (as fnmatch globs) and categories (tests, docs, infra, config, code) the task is allowed to touch.
- Actual diff — the files the AI actually modified.
If the actual diff exceeds the declared scope, the tool returns status=over_reach and lists the offending files and categories.
What this tool does and does not do
over-reach-detector is an audit/disclosure tool, not a sandbox and not a blocker.
It compares a declared task scope with the actual files/categories changed by an AI coding agent. If the actual changes exceed the declared scope, it reports that mismatch.
It does not prevent file writes by itself. It does not decide whether to revert, approve, or block a change. The caller remains responsible for enforcement, rollback, or human review.
Install
From PyPI:
pip install over-reach-detector
From source:
git clone https://github.com/choreoatlas/over_reach_detector
cd over_reach_detector
pip install -e .
Quick start
Run all tests: python -m pytest -v
Try the CLI directly: python -m over_reach_detector.detector --input fixtures/example_pr_1.json --format markdown
Use as MCP server
Start the server (stdio transport): over-reach-detector (or python -m over_reach_detector.server from source)
Register with your AI agent:
- Cursor: in
~/.cursor/mcp.json, add (afterpip install over-reach-detector):
{
"mcpServers": {
"over-reach-detector": {
"command": "over-reach-detector"
}
}
}
Dev / from source: use "command": "python", "args": ["-m", "over_reach_detector.server"] (run from repo root).
- Claude Code: after
pip install over-reach-detector, runclaude mcp add over-reach-detector over-reach-detector(writes to~/.claude.json). Dev / from source:claude mcp add over-reach-detector /absolute/path/to/python -m over_reach_detector.server.
The tool
check_scope_tool takes:
declared_files: list of fnmatch globs (e.g.["docs/*.md", "tests/*.py"])declared_categories: subset of["tests", "docs", "infra", "config", "code"]actual_files: list of file paths the AI modifiedoutput_format:"json"(default) or"markdown"
Returns a report with:
status:in_scope(within declared scope) |over_reach(reported mismatch) |emptyfile_overreach: files not matching any declared globcategory_overreach: inferred categories outside the declared set
Scope discipline
Current scope: CLI + MCP stdio server + 1 tool. Python only. fnmatch-based globs.
Out of scope (forbidden): code quality review, security audit, completeness governance, languages other than Python, multi-tool MCP servers, HTTP/SSE transport, GitHub Actions integration. These are deliberately deferred to later versions or never.
Example usage
Call check_scope_tool directly from Python (same logic the MCP server exposes):
import json
from over_reach_detector import server
result = server.check_scope_tool(
declared_files=["docs/*.md"],
declared_categories=["docs"],
actual_files=["docs/a.md", "scripts/extra.py"],
output_format="json",
)
report = json.loads(result)
print(report["status"]) # "over_reach"
print(report["file_overreach"]) # ["scripts/extra.py"]
License
MIT — see LICENSE.
Questions fréquentes
Qu'est-ce que Over-Reach Detector ?
Detect when AI code changes exceed declared task scope (MCP server).
Comment installer Over-Reach Detector ?
Il s'exécute sur votre machine. Dans Claude Code : claude mcp add over-reach-detector -- uvx over-reach-detector==0.0.6. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour Over-Reach Detector ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
Over-Reach Detector est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient Over-Reach Detector ?
Il est publié par choreoatlas. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.